Advanced healthcare monitors for air pollution applications pose a significant challenge in achieving a balance between high-performance filtration and multifunctional smart integration.Electrospinning triboelectric n...Advanced healthcare monitors for air pollution applications pose a significant challenge in achieving a balance between high-performance filtration and multifunctional smart integration.Electrospinning triboelectric nanogenerators(TENG)provide a significant potential for use under such difficult circumstances.We have successfully constructed a high-performance TENG utilizing a novel multi-scale nanofiber architecture.Nylon 66(PA66)and chitosan quaternary ammonium salt(HACC)composites were prepared by electrospinning,and PA66/H multiscale nanofiber membranes composed of nanofibers(≈73 nm)and submicron-fibers(≈123 nm)were formed.PA66/H multi-scale nanofiber membrane as the positive electrode and negative electrode-spun PVDF-HFP nanofiber membrane composed of respiration-driven PVDF-HFP@PA66/H TENG.The resulting PVDF-HFP@PA66/H TENG based air filter utilizes electrostatic adsorption and physical interception mechanisms,achieving PM_(0.3)filtration efficiency over 99%with a pressure drop of only 48 Pa.Besides,PVDF-HFP@PA66/H TENG exhibits excellent stability in high-humidity environments,with filtration efficiency reduced by less than 1%.At the same time,the TENG achieves periodic contact separation through breathing drive to achieve self-power,which can ensure the long-term stability of the filtration efficiency.In addition to the air filtration function,TENG can also monitor health in real time by capturing human breathing signals without external power supply.This integrated system combines high-efficiency air filtration,self-powered operation,and health monitoring,presenting an innovative solution for air purification,smart protective equipment,and portable health monitoring.These findings highlight the potential of this technology for diverse applications,offering a promising direction for advancing multifunctional air filtration systems.展开更多
Natural polymers possess the qualities of abundant resources,low cost,as well as excellent biocompatibility and biodegradability,and are ideal materials for next-generation wearable and portable electronic devices.To ...Natural polymers possess the qualities of abundant resources,low cost,as well as excellent biocompatibility and biodegradability,and are ideal materials for next-generation wearable and portable electronic devices.To further augment the application scope of natural polymer materials,integrating them with functional materials represents a promising approach that is of great value for the sustainable development of triboelectric nanogenerators.Here,we successfully synthesized starch-[CsPbBr_(3)-KBr]-Fe_(3)O_(4)composite films through the combination of natural polymer materials with magnetic and fluorescent components.It is capable of achieving reversible hydrochromic conversion by exposing or removing water.The combination of fluorescent CsPbBr_(3)-KBr,magnetic Fe_(3)O_(4),and waterproof starch-[CsPbBr_(3)-KBr]-Fe_(3)O_(4)-Polydimethylsiloxane leads to the realization of fluorescence and magnetic composite anti-counterfeiting.This composite anti-counterfeiting technology presents a novel and highly effective approach for ensuring the authenticity and security of various types of information.In addition,the Composite film based triboelectric nanogenerator has been assembled,which has a stable output with a short circuit current and open-circuit voltage of 15.1μA and 170.1 V,respectively.The triboelectric nanogenerator can light 204 red LED lights at the same time,and the electrical output is not reduced even after 4200 mechanical cycles.Furthermore,based on the triboelectric nanogenerator,we have successfully demonstrated a self-powered sensor that can monitor human movement signals in real time.The sensor has shown broad application prospects in the field of health monitoring and motion analysis.展开更多
Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reas...Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.展开更多
Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability challenges.These systems facilitate informed decisions that enhance efficiency in broader environmental management...Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability challenges.These systems facilitate informed decisions that enhance efficiency in broader environmental management.Existing outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex structures.Herein,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by it.It can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous operation.Moreover,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption methods.Its potential extends to acting as other self-powered environmental sensors.This multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.展开更多
This study explores how the performance of triboelectric nanogenerators can be enhanced by incorporating Fe_(3)O_(4) nanoparticles into nylon films using a spray coating technique.Five triboelectric nanogenerator prot...This study explores how the performance of triboelectric nanogenerators can be enhanced by incorporating Fe_(3)O_(4) nanoparticles into nylon films using a spray coating technique.Five triboelectric nanogenerator prototypes were created:one with regular nylon and four with nylon/Fe_(3)O_(4) nanocomposites featuring varying nanoparticle densities.The electrical output,measured by open-circuit voltage and short-circuit current,showed significant improvements in the nanocomposite-based triboelectric nanogenerators compared to the nylon-only triboelectric nanogenerator.When a weak magnetic field was applied during nanocomposite preparation,the maximum voltage and current reached 56.3 V and 4.62μA,respectively.Further analysis revealed that the magnetic field during the drying process aligned the magnetic domains,boosting output efficiency.These findings demonstrate the potential of Fe_(3)O_(4) nanoparticles to enhance electrostatic and magnetic interactions in triboelectric nanogenerators,leading to improved energy-harvesting performance.This approach presents a promising strategy for developing high-performance triboelectric nanogenerators for sustainable energy and sensor applications.展开更多
This paper aims to study a novel smart self-powered wireless lightweight (SPWL) bridge health monitoring sensor, which integrates key technologies such as large-scale, low-power wireless data transmission, environment...This paper aims to study a novel smart self-powered wireless lightweight (SPWL) bridge health monitoring sensor, which integrates key technologies such as large-scale, low-power wireless data transmission, environmental energy self-harvesting, and intelligent perception, and can operate stably for a long time in complex and changing environments. The self-powered system of the sensor can meet the needs of long-term bridge service performance monitoring, significantly improving the coverage and efficiency of monitoring. By optimizing the sensor system design, the maximum energy conversion of the energy harvesting unit is achieved. In order to verify the function and practicality of the new SPWL monitoring sensor, this study combined the actual bridge engineering, carried out a bridge monitoring case study, and developed an SPWL monitoring scheme based on the bridge structure principle. Compared with traditional monitoring methods, this technology significantly improves the sustainability and performance of infrastructure monitoring based on the new SPWL sensor, fully demonstrating the excellent monitoring capabilities of this type of sensor, and providing strong support for the development of intelligent transportation and intelligent infrastructure.展开更多
Targeting spontaneous coal combustion during stacking,we developed an efficient heat dissipation&self-supplied wireless temperature measurement system(SPWTM)with gravity heat pipe-thermoelectric integration for du...Targeting spontaneous coal combustion during stacking,we developed an efficient heat dissipation&self-supplied wireless temperature measurement system(SPWTM)with gravity heat pipe-thermoelectric integration for dual safety.The heat transfer characteristics and temperature measurement optimization of the system are experimentally investigated and verified in practical applications.The results show that,firstly,the effects of coal pile heat production power and burial depth,along with heat pipe startup and heat transfer characteristics.At 60 cmburial depth,the condensation section dissipates 98%coal pile heat via natural convection.Secondly,for the temperature measurement error caused by the heat pipe heat transfer temperature difference,the correction method of“superimposing the measured value with the heat transfer temperature difference”is proposed,and the higher the coal temperature,the better the temperature measurement accuracy.Finally,the system can quickly(≤1 h)reduce the temperature of the coal pile to the spontaneous combustion point,significantly inhibiting the spontaneous combustion phenomenon,the maximum temperature does not exceed 49.2℃.Meanwhile,it utilizes waste heat to drive thermoelectric power generation,realizing self-supplied,unattended,and long-term accurate temperature measurement and warning.In a word,synergistic active heat dissipation and self-powered temperature monitoring-warning ensure dual coal pile thermal safety.展开更多
With the continuous advancement of social technology and the increasing awareness of health management,biomass-based triboelectric nanogenerator(TENG)displayed significant potential as flexible wearable electronics fo...With the continuous advancement of social technology and the increasing awareness of health management,biomass-based triboelectric nanogenerator(TENG)displayed significant potential as flexible wearable electronics for continuous foot gait monitoring.Nevertheless,existing biomass-based TENG often faces challenges of insufficient mechanical robustness and durability in practical applications,where they are prone to surface abrasion and structural fracture under continuous compression and friction,severely limiting their long-term performances.In order to address these challenges,this work proposed a multiscale crosslinking strategy,which strengthened the noncovalent interactions within the polymer by constructing multiple reinforcement networks,successfully fabricating a dual-network C-lignin-based triboelectric material(CLTM)with excellent durability and crack resistance.Among them,the optimal CLTM(PSGCL-0.2)exhibited high mechanical strength(strain 445%,tensile strength 41.56 MPa,Young's modulus 41.25 MPa,toughness 159.67 MJ/m^(3))and excellent cyclic stability(300 cycles)with versatile functionalities,including antibacterial,antioxidant,and UV-shielding properties,water stabilization(255.51 g/m^(2)/d),efficient photothermal conversion,and full recyclability.Furthermore,biomass-based TENG device assembled from PSGCL-0.2 achieved stable triboelectric output properties(102.5 V,2.9μA,and 61.3 nC),and sustainable for 2000 cycles,fast response time(68 ms),and excellent power density(325.9 mW/m^(2)),effectively converting mechanical energy into electrical energy.Especially,PSGCL 0.2 was also integrated into the wireless self-powered smart insole,successfully enabling real-time visual monitoring of plantar pressure distribution and dynamic gait.Meanwhile,combined with the machine learning algorithm,the self-powered smart insole achieved precise recognition and classification of eight different motion states with an accuracy of 98%.This study provides the feasible strategy for developing extremely stable and durable biomass-based TENG,aimed at advancing sustainable intelligent healthcare systems.展开更多
Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ion...Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.展开更多
To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail stee...To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge.An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns.XGBoost(eXtreme Gradient Boosting),a gradient-boosting machine learning(ML)algorithm,was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution.Unlike traditional numerical models that rely on extensive assumptions and idealizations,XGBoost effectively captures nonlinear and time-varying relationships between stress states and operational/environmental factors,such as temperature,traffic load,and structural geometry.This approach allows for the identification of critical periods and conditions under which stress redistribution becomes significant.Results indicate a clear shift of stress concentrations frombeamends toward mid-span regions following the commencement of metro operations,reflecting both structural adaptation and localized overstress near arch ribs.Furthermore,the model generates robust predictions of stress evolution,demonstrating potential applications in early warning systems and fatigue risk assessment.This work represents the first application of interpretable gradient-boosting techniques to stress redistribution modeling in double-deck bridges.In addition,a Stress Redistribution Index(SRI)is proposed,derived from this monitoring study and finite-element-based transverse load distributions,to quantify temporal stress shifts between midspan and edge beams.The results provide both theoretical contributions and practical guidance for the design,inspection,and maintenance of complex bridge structures.展开更多
The rapid advancement of flexible electronics technology has placed higher demands on the structural design and performance regulation of elastic materials.Cellulosic elastomers,with their biodegradability,renewabilit...The rapid advancement of flexible electronics technology has placed higher demands on the structural design and performance regulation of elastic materials.Cellulosic elastomers,with their biodegradability,renewability,and tunability,emerge as ideal candidate materials.Entropy-driven self-as sembly promotes the spontaneous formation of ordered structures,serving as a crucial pathway for optimizing cellulose elastomer properties.However,the structure-property relationship between the self-assembled ordered structures of cellulose elastomers and their mechanical and electrical properties remains insufficiently explored.It hinders the expansion of their applications in electronic devices.This paper systematically reviews the structure-property regulation mechanisms of self-assembled cellulosic elastomers from an entropy-driven perspective.It elucidates the application principles and performance optimization strategies for mechanical energy harvesting and self-powered sensing,while also exploring the challenges and prospects for performance enhancement.This work provides a reference for the development of self-assembled cellulosic elastomers in the field of energy devices.展开更多
An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings...Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.展开更多
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge gen...To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.展开更多
A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without in...A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.展开更多
Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properti...Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properties,offer unique advantages for creating next-generation personalized devices.In recent years,flexible polymer-based platforms have shown remarkable potential to capture diverse physiological signals in both daily and clinical contexts,including electrophysiological,biochemical,mechanical,and thermal indicators.In this review,we introduce a safety-leveloriented framework to evaluate material and device strategies for health monitoring,spanning the continuum from noninvasive wearables to deeply embedded implants.Physiological signals are systematically classified by use case,and application-specific requirements such as stability,comfort,and long-term compatibility are highlighted as critical factors guiding the selection of polymers,interfacial designs,and device architectures.Special emphasis is placed on mapping material types—including hydrogels,elastomers,and conductive composites—to their most suitable applications.Finally,we propose design principles for developing safe,functional,and adaptive polymer-based systems,aiming at reliable integration with the human body and enabling personalized,preventive healthcare.展开更多
Satellite hydrology has reached a new era where a variety of earth observing systems,in conjunction with the development of data integrations,can provide a consistent monitoring of groundwater change,wetland dynamics,...Satellite hydrology has reached a new era where a variety of earth observing systems,in conjunction with the development of data integrations,can provide a consistent monitoring of groundwater change,wetland dynamics,and drought evolution in regions where observations on the ground remain sparse or patchy.This synthesis review highlights the physical observables that are most useful to terrestrial hydrology:variable time-dependent gravity,passive and active microwave signals,optical reflectance,thermal infrared measurements,and altimetry,and this has been translated into hydrologic states and water fluxes:terrestrial water storage,ground water storage anomalies,inundation extent and hydroperiod,evapotranspiration,and multi-timescale drought indicators.We call attention to the role of satellite gravimetry in the transformation of basin-scale groundwater evaluation,synthetic aperture radar(SAR),and optical time series in transforming wetland science,however,to the characterization of hydroperiod and connectivity.In the case of drought,we recommend the use of both fast-responsive(soil moisture,evapotranspiration,thermal stress,and vegetation condition)in conjunction with slowly integrating storage anomalies to detect onset,intensification,and recovery,as well as rely on to diagnose the spread of deficits through the hydrologic system.In all these themes,we recognize the central action of enabling approaches that include multi-sensor fusion,data assimilation,and hybrid machine learning schemes in reducing ambiguity,scale gaps,and producing products of decision interest,and also highlighting ongoing issues in the quantification of uncertainty,consistency across long periods of time,and the separation of climate influence on human management of water.Research and operational priorities come as our final deduction to develop satellite hydrology to more trustworthy,explanation-seeking,and operationalizing monitoring designs of water security and ecosystem resilience.展开更多
The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warni...The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warning model based on multi-parameter fuzzy comprehensive evaluation,which quantitatively assesses the risk state of the surrounding rock mass.The microseismic(MS)monitoring system is set up for the underground powerhouse.The spatial and temporal distribution of MS events and the frequency characteristics of MS signals are analyzed during the top arch excavation.The early warning indices for characterizing MS spatial aggregation and frequency-energy dispersion are proposed based on the octree theory to assess the deformation of the surrounding rock mass.The risk warning model for the surrounding rock mass in underground engineering is developed through the integration of the formulated index and the frequency characteristics of MS signals.The results indicate that the multiparameter fuzzy comprehensive assessment model can achieve three-dimensional visualization of risk warnings for the surrounding rock mass.The quantitative results regarding warning time and potential deformation areas are highly consistent with the characteristics of MS precursors.These research results can provide an important reference for early warning of surrounding rock mass risk in similar underground projects.展开更多
Ensuring an information fabric safe is critical and mandatory.For its related Internet of Things(IoT)service system running on the open Internet,existing host-based monitoring methods may fail due to only inspecting s...Ensuring an information fabric safe is critical and mandatory.For its related Internet of Things(IoT)service system running on the open Internet,existing host-based monitoring methods may fail due to only inspecting software,and the physical system may not be able to be protected.In this paper,a nonintrusive virtual machine(VM)-based runtime protection framework is provided to protect the physical system with the isolated IoT services as a controlling means.Compared with existing solutions,the framework gets inconsistent and untrusted observation knowledge from multiple observation sources,and enforces property policies concurrently and incrementally in a competing-game way to avoid compositional problems.In addition,the monitoring is implemented without any modification to the protected system.Experiments are conducted to validate the proposed techniques.展开更多
基金financial support from the National Key Research and Development Program of China(2022YFB3804905)National Natural Science Foundation of China(22375047,22378068,and 22378071)+1 种基金Natural Science Foundation of Fujian Province(2022J01568)111 Project(No.D17005).
文摘Advanced healthcare monitors for air pollution applications pose a significant challenge in achieving a balance between high-performance filtration and multifunctional smart integration.Electrospinning triboelectric nanogenerators(TENG)provide a significant potential for use under such difficult circumstances.We have successfully constructed a high-performance TENG utilizing a novel multi-scale nanofiber architecture.Nylon 66(PA66)and chitosan quaternary ammonium salt(HACC)composites were prepared by electrospinning,and PA66/H multiscale nanofiber membranes composed of nanofibers(≈73 nm)and submicron-fibers(≈123 nm)were formed.PA66/H multi-scale nanofiber membrane as the positive electrode and negative electrode-spun PVDF-HFP nanofiber membrane composed of respiration-driven PVDF-HFP@PA66/H TENG.The resulting PVDF-HFP@PA66/H TENG based air filter utilizes electrostatic adsorption and physical interception mechanisms,achieving PM_(0.3)filtration efficiency over 99%with a pressure drop of only 48 Pa.Besides,PVDF-HFP@PA66/H TENG exhibits excellent stability in high-humidity environments,with filtration efficiency reduced by less than 1%.At the same time,the TENG achieves periodic contact separation through breathing drive to achieve self-power,which can ensure the long-term stability of the filtration efficiency.In addition to the air filtration function,TENG can also monitor health in real time by capturing human breathing signals without external power supply.This integrated system combines high-efficiency air filtration,self-powered operation,and health monitoring,presenting an innovative solution for air purification,smart protective equipment,and portable health monitoring.These findings highlight the potential of this technology for diverse applications,offering a promising direction for advancing multifunctional air filtration systems.
基金supported by the Key Research Program of Frontier Sciences,CAS,China(ZDBS-LY-DQC025)the Basic Scientific Research Project of the National Institute of Metrology,China(AKYZZ2449,AKYZZ2546).
文摘Natural polymers possess the qualities of abundant resources,low cost,as well as excellent biocompatibility and biodegradability,and are ideal materials for next-generation wearable and portable electronic devices.To further augment the application scope of natural polymer materials,integrating them with functional materials represents a promising approach that is of great value for the sustainable development of triboelectric nanogenerators.Here,we successfully synthesized starch-[CsPbBr_(3)-KBr]-Fe_(3)O_(4)composite films through the combination of natural polymer materials with magnetic and fluorescent components.It is capable of achieving reversible hydrochromic conversion by exposing or removing water.The combination of fluorescent CsPbBr_(3)-KBr,magnetic Fe_(3)O_(4),and waterproof starch-[CsPbBr_(3)-KBr]-Fe_(3)O_(4)-Polydimethylsiloxane leads to the realization of fluorescence and magnetic composite anti-counterfeiting.This composite anti-counterfeiting technology presents a novel and highly effective approach for ensuring the authenticity and security of various types of information.In addition,the Composite film based triboelectric nanogenerator has been assembled,which has a stable output with a short circuit current and open-circuit voltage of 15.1μA and 170.1 V,respectively.The triboelectric nanogenerator can light 204 red LED lights at the same time,and the electrical output is not reduced even after 4200 mechanical cycles.Furthermore,based on the triboelectric nanogenerator,we have successfully demonstrated a self-powered sensor that can monitor human movement signals in real time.The sensor has shown broad application prospects in the field of health monitoring and motion analysis.
基金supported by the National Natural Science Foundation of China(Nos.12172248,12302022,12021002,and 12132010)the Tianjin Research Program of Application Foundation and Advanced Technology of China(No.23JCZDJC00950)。
文摘Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.
基金supported by the Research Platform for biomedical and Health Technology, NUS (Suzhou) Research Institute (RP-BHT-Prof. LEE Chengkuo)RIE Advanced Manufacturing and Engineering (AME) Programmatic Grant (Grant A18A4b0055)+1 种基金RIE 2025-Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) (Grant I2301E0027)Reimagine Research Scheme projects, National University of Singapore, A-0009037-03-00 and A-0009454-01-00 and Reimagine Research Scheme projects, National University of Singapore, A-0004772-00-00 and A-0004772-01-00。
文摘Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability challenges.These systems facilitate informed decisions that enhance efficiency in broader environmental management.Existing outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex structures.Herein,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by it.It can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous operation.Moreover,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption methods.Its potential extends to acting as other self-powered environmental sensors.This multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.
文摘This study explores how the performance of triboelectric nanogenerators can be enhanced by incorporating Fe_(3)O_(4) nanoparticles into nylon films using a spray coating technique.Five triboelectric nanogenerator prototypes were created:one with regular nylon and four with nylon/Fe_(3)O_(4) nanocomposites featuring varying nanoparticle densities.The electrical output,measured by open-circuit voltage and short-circuit current,showed significant improvements in the nanocomposite-based triboelectric nanogenerators compared to the nylon-only triboelectric nanogenerator.When a weak magnetic field was applied during nanocomposite preparation,the maximum voltage and current reached 56.3 V and 4.62μA,respectively.Further analysis revealed that the magnetic field during the drying process aligned the magnetic domains,boosting output efficiency.These findings demonstrate the potential of Fe_(3)O_(4) nanoparticles to enhance electrostatic and magnetic interactions in triboelectric nanogenerators,leading to improved energy-harvesting performance.This approach presents a promising strategy for developing high-performance triboelectric nanogenerators for sustainable energy and sensor applications.
文摘This paper aims to study a novel smart self-powered wireless lightweight (SPWL) bridge health monitoring sensor, which integrates key technologies such as large-scale, low-power wireless data transmission, environmental energy self-harvesting, and intelligent perception, and can operate stably for a long time in complex and changing environments. The self-powered system of the sensor can meet the needs of long-term bridge service performance monitoring, significantly improving the coverage and efficiency of monitoring. By optimizing the sensor system design, the maximum energy conversion of the energy harvesting unit is achieved. In order to verify the function and practicality of the new SPWL monitoring sensor, this study combined the actual bridge engineering, carried out a bridge monitoring case study, and developed an SPWL monitoring scheme based on the bridge structure principle. Compared with traditional monitoring methods, this technology significantly improves the sustainability and performance of infrastructure monitoring based on the new SPWL sensor, fully demonstrating the excellent monitoring capabilities of this type of sensor, and providing strong support for the development of intelligent transportation and intelligent infrastructure.
基金supported by the Engineering Research Centre for Digital Grid Technology for Coordinating New Energy under Grant[Grant number 2021GCZX003]Yunnan Fundamental Research Projects under Grant[Grant number 202301CF070031]+2 种基金Hundred Talents Project 2023 under Grant[Grant number B0201001]2024 Distinctive Innovation Scientific Research Projects for Higher Education Institutions[Grant number 2024KTSCX157]Young Innovative Talent Project under Grant[Grant numbers K0223021,K0224014].
文摘Targeting spontaneous coal combustion during stacking,we developed an efficient heat dissipation&self-supplied wireless temperature measurement system(SPWTM)with gravity heat pipe-thermoelectric integration for dual safety.The heat transfer characteristics and temperature measurement optimization of the system are experimentally investigated and verified in practical applications.The results show that,firstly,the effects of coal pile heat production power and burial depth,along with heat pipe startup and heat transfer characteristics.At 60 cmburial depth,the condensation section dissipates 98%coal pile heat via natural convection.Secondly,for the temperature measurement error caused by the heat pipe heat transfer temperature difference,the correction method of“superimposing the measured value with the heat transfer temperature difference”is proposed,and the higher the coal temperature,the better the temperature measurement accuracy.Finally,the system can quickly(≤1 h)reduce the temperature of the coal pile to the spontaneous combustion point,significantly inhibiting the spontaneous combustion phenomenon,the maximum temperature does not exceed 49.2℃.Meanwhile,it utilizes waste heat to drive thermoelectric power generation,realizing self-supplied,unattended,and long-term accurate temperature measurement and warning.In a word,synergistic active heat dissipation and self-powered temperature monitoring-warning ensure dual coal pile thermal safety.
基金supported by the grants from National Natural Science Foundation of China(Nos.22278091,22278046)Young Elite Sci-entists Sponsorship Program by CAST(No.2024QNRC0387)+2 种基金the Guangxi Natural Science Foundation of China(Nos.2025GXNSFBA069146,2023GXNSFGA026001,GKAD25069076)the Foundation(No.202403)of Tianjin Key Laboratory of Pulp&Paper(Tianjin University of Science&Technology)P.R.China,and the Foundation of Guangxi Key Laboratory of Clean Pulp&Papermaking and Pollution Control,College of Light Industry and Food Engineering,Guangxi University(No.2021KF01).
文摘With the continuous advancement of social technology and the increasing awareness of health management,biomass-based triboelectric nanogenerator(TENG)displayed significant potential as flexible wearable electronics for continuous foot gait monitoring.Nevertheless,existing biomass-based TENG often faces challenges of insufficient mechanical robustness and durability in practical applications,where they are prone to surface abrasion and structural fracture under continuous compression and friction,severely limiting their long-term performances.In order to address these challenges,this work proposed a multiscale crosslinking strategy,which strengthened the noncovalent interactions within the polymer by constructing multiple reinforcement networks,successfully fabricating a dual-network C-lignin-based triboelectric material(CLTM)with excellent durability and crack resistance.Among them,the optimal CLTM(PSGCL-0.2)exhibited high mechanical strength(strain 445%,tensile strength 41.56 MPa,Young's modulus 41.25 MPa,toughness 159.67 MJ/m^(3))and excellent cyclic stability(300 cycles)with versatile functionalities,including antibacterial,antioxidant,and UV-shielding properties,water stabilization(255.51 g/m^(2)/d),efficient photothermal conversion,and full recyclability.Furthermore,biomass-based TENG device assembled from PSGCL-0.2 achieved stable triboelectric output properties(102.5 V,2.9μA,and 61.3 nC),and sustainable for 2000 cycles,fast response time(68 ms),and excellent power density(325.9 mW/m^(2)),effectively converting mechanical energy into electrical energy.Especially,PSGCL 0.2 was also integrated into the wireless self-powered smart insole,successfully enabling real-time visual monitoring of plantar pressure distribution and dynamic gait.Meanwhile,combined with the machine learning algorithm,the self-powered smart insole achieved precise recognition and classification of eight different motion states with an accuracy of 98%.This study provides the feasible strategy for developing extremely stable and durable biomass-based TENG,aimed at advancing sustainable intelligent healthcare systems.
基金National Natural Science Foundation of China(NSFC,No.22131008)Natural Science Foundation of Tianjin(No.22JCYBJC00500)the Haihe Laboratory of Sustainable Chemical Transformations for financial support.
文摘Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.
基金supported by the Key Technologies Research and Development Program under Grant 2021YFB1600300.
文摘To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge.An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns.XGBoost(eXtreme Gradient Boosting),a gradient-boosting machine learning(ML)algorithm,was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution.Unlike traditional numerical models that rely on extensive assumptions and idealizations,XGBoost effectively captures nonlinear and time-varying relationships between stress states and operational/environmental factors,such as temperature,traffic load,and structural geometry.This approach allows for the identification of critical periods and conditions under which stress redistribution becomes significant.Results indicate a clear shift of stress concentrations frombeamends toward mid-span regions following the commencement of metro operations,reflecting both structural adaptation and localized overstress near arch ribs.Furthermore,the model generates robust predictions of stress evolution,demonstrating potential applications in early warning systems and fatigue risk assessment.This work represents the first application of interpretable gradient-boosting techniques to stress redistribution modeling in double-deck bridges.In addition,a Stress Redistribution Index(SRI)is proposed,derived from this monitoring study and finite-element-based transverse load distributions,to quantify temporal stress shifts between midspan and edge beams.The results provide both theoretical contributions and practical guidance for the design,inspection,and maintenance of complex bridge structures.
基金supported by the National Natural Science Foundation of China(32571991)Guangxi Natural Science Foundation of China(2023GXNSFGA026001&2025GXNSFAA069870)the Foundation of State Key Laboratory of Biobased Material and Green Papermaking.(No.GZKF202323)。
文摘The rapid advancement of flexible electronics technology has placed higher demands on the structural design and performance regulation of elastic materials.Cellulosic elastomers,with their biodegradability,renewability,and tunability,emerge as ideal candidate materials.Entropy-driven self-as sembly promotes the spontaneous formation of ordered structures,serving as a crucial pathway for optimizing cellulose elastomer properties.However,the structure-property relationship between the self-assembled ordered structures of cellulose elastomers and their mechanical and electrical properties remains insufficiently explored.It hinders the expansion of their applications in electronic devices.This paper systematically reviews the structure-property regulation mechanisms of self-assembled cellulosic elastomers from an entropy-driven perspective.It elucidates the application principles and performance optimization strategies for mechanical energy harvesting and self-powered sensing,while also exploring the challenges and prospects for performance enhancement.This work provides a reference for the development of self-assembled cellulosic elastomers in the field of energy devices.
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金supported by the Research Funding Project for Graduate Education and Teaching Reform of Beijing University of Posts and Telecommunications(No.2024Y036)the Postgraduate Education and Teaching Reform Research Fund Project of Beijing University of Posts and Telecommunications(No.2024Z007)the Postgraduate Education and Teaching Reform Project of Beijing University of Posts and Telecommunications(2025).
文摘Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
基金supported by the National Key Research and Development Project of the National Natural Science Foundation of China(Grant No.2022YFC3004605)the National Natural Science Foundation of China Youth Science Fund(Grant No.52104087).
文摘To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.
基金supported by the National Natural Science Foundation of China(22074072,22274083,52376199)the Shandong Provincial Natural Science Foundation(ZR2023LZY005)+1 种基金the Exploration Project of the State Key Laboratory of BioFibers and EcoTextiles of Qingdao University(TSKT202101)the Fundamental Research Funds for the Central Universities(2022BLRD13,2023BLRD01).
文摘A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.
基金the financial support from the National University of Singapore(Grant No.A-001002800-00)the Singapore Ministry of Education(Grant No.A-8003587-00-00)。
文摘Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properties,offer unique advantages for creating next-generation personalized devices.In recent years,flexible polymer-based platforms have shown remarkable potential to capture diverse physiological signals in both daily and clinical contexts,including electrophysiological,biochemical,mechanical,and thermal indicators.In this review,we introduce a safety-leveloriented framework to evaluate material and device strategies for health monitoring,spanning the continuum from noninvasive wearables to deeply embedded implants.Physiological signals are systematically classified by use case,and application-specific requirements such as stability,comfort,and long-term compatibility are highlighted as critical factors guiding the selection of polymers,interfacial designs,and device architectures.Special emphasis is placed on mapping material types—including hydrogels,elastomers,and conductive composites—to their most suitable applications.Finally,we propose design principles for developing safe,functional,and adaptive polymer-based systems,aiming at reliable integration with the human body and enabling personalized,preventive healthcare.
文摘Satellite hydrology has reached a new era where a variety of earth observing systems,in conjunction with the development of data integrations,can provide a consistent monitoring of groundwater change,wetland dynamics,and drought evolution in regions where observations on the ground remain sparse or patchy.This synthesis review highlights the physical observables that are most useful to terrestrial hydrology:variable time-dependent gravity,passive and active microwave signals,optical reflectance,thermal infrared measurements,and altimetry,and this has been translated into hydrologic states and water fluxes:terrestrial water storage,ground water storage anomalies,inundation extent and hydroperiod,evapotranspiration,and multi-timescale drought indicators.We call attention to the role of satellite gravimetry in the transformation of basin-scale groundwater evaluation,synthetic aperture radar(SAR),and optical time series in transforming wetland science,however,to the characterization of hydroperiod and connectivity.In the case of drought,we recommend the use of both fast-responsive(soil moisture,evapotranspiration,thermal stress,and vegetation condition)in conjunction with slowly integrating storage anomalies to detect onset,intensification,and recovery,as well as rely on to diagnose the spread of deficits through the hydrologic system.In all these themes,we recognize the central action of enabling approaches that include multi-sensor fusion,data assimilation,and hybrid machine learning schemes in reducing ambiguity,scale gaps,and producing products of decision interest,and also highlighting ongoing issues in the quantification of uncertainty,consistency across long periods of time,and the separation of climate influence on human management of water.Research and operational priorities come as our final deduction to develop satellite hydrology to more trustworthy,explanation-seeking,and operationalizing monitoring designs of water security and ecosystem resilience.
基金support from the Sichuan Science and Technology Program(Grant No.2023NSFSC0812).
文摘The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warning model based on multi-parameter fuzzy comprehensive evaluation,which quantitatively assesses the risk state of the surrounding rock mass.The microseismic(MS)monitoring system is set up for the underground powerhouse.The spatial and temporal distribution of MS events and the frequency characteristics of MS signals are analyzed during the top arch excavation.The early warning indices for characterizing MS spatial aggregation and frequency-energy dispersion are proposed based on the octree theory to assess the deformation of the surrounding rock mass.The risk warning model for the surrounding rock mass in underground engineering is developed through the integration of the formulated index and the frequency characteristics of MS signals.The results indicate that the multiparameter fuzzy comprehensive assessment model can achieve three-dimensional visualization of risk warnings for the surrounding rock mass.The quantitative results regarding warning time and potential deformation areas are highly consistent with the characteristics of MS precursors.These research results can provide an important reference for early warning of surrounding rock mass risk in similar underground projects.
基金supported by the National Key Research and Development Program of China under grant 2022YFF0902701the National Natural Science Foundation of China under grant U21A20468,61972043,61921003+1 种基金Zhejiang Lab under grant 2021PD0AB 02the Fundamental Research Funds for the Central Universities under grant 2020XD-A07-1.
文摘Ensuring an information fabric safe is critical and mandatory.For its related Internet of Things(IoT)service system running on the open Internet,existing host-based monitoring methods may fail due to only inspecting software,and the physical system may not be able to be protected.In this paper,a nonintrusive virtual machine(VM)-based runtime protection framework is provided to protect the physical system with the isolated IoT services as a controlling means.Compared with existing solutions,the framework gets inconsistent and untrusted observation knowledge from multiple observation sources,and enforces property policies concurrently and incrementally in a competing-game way to avoid compositional problems.In addition,the monitoring is implemented without any modification to the protected system.Experiments are conducted to validate the proposed techniques.
